ArticleAnalytical chemistry2022
Addressing Missing Data in GC × GC Metabolomics: Identifying Missingness Type and Evaluating the Impact of Imputation Methods on Experimental Replication.
Article in Analytical chemistry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- A Reporting Guideline for Observational Studies in Metabolomic Epidemiology: Explanation and Elaboration of the Strobe-MetEpi Checklist.Research square · 2026Article
- High-Throughput Suspect Screening Reveals Widespread Pesticide Exposure in Early Childhood.Environment & health (Washington, D.C.) · 2026Article
- Bayesian Sparse Regression for Microbiome-Metabolite Data Integration.Statistics in medicine · 2026Article
- Integrating Metabolomics and Machine Learning for Advanced Chemical Detection.Sensors (Basel, Switzerland) · 2026Review
- Retrospective analysis of the epidemiological characteristics, risk factors, survival rate, and drug resistance of candidemia and construction of a logistic regression prediction model (2013-2024).BMC infectious diseases · 2026Article
- Article
- Polar Metabolite Profiles Distinguish Between Early and Severe Sub-Maintenance Nutritional States of Wild Bighorn Sheep.Metabolites · 2025Article
- CE-MS-Based Clinical Metabolomics of Human Plasma.Methods in molecular biology (Clifton, N.J.) · 2025Article
- imputomics: web server and R package for missing values imputation in metabolomics data.Bioinformatics (Oxford, England) · 2024Article
- Statistical methods and resources for biomarker discovery using metabolomics.BMC bioinformatics · 2023Review
- Comprehensive Two-Dimensional Gas Chromatography as a Bioanalytical Platform for Drug Discovery and Analysis.Pharmaceutics · 2023Review
- Big Data in Gastroenterology Research.International journal of molecular sciences · 2023Review
- Volatile Metabolites in Lavage Fluid Are Correlated with Cytokine Production in a Valley Fever Murine Model.Journal of fungi (Basel, Switzerland) · 2023Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
Abstract
Missing data is a significant issue in metabolomics that is often neglected when conducting data preprocessing, particularly when it comes to imputation. This can have serious implications for downstream statistical analyses and lead to misleading or uninterpretable inferences. In this study, we aim to identify the primary types of missingness that affect untargeted metabolomics data and compare strategies for imputation using two real-world comprehensive two-dimensional gas chromatography (GC × GC) data sets. We also present these goals in the context of experimental replication whereby imputation is conducted in a within-replicate-based fashion─the first description and evaluation of this strategy─and introduce an R package
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.